Why China maintained its strong economic growth

Introduction

China’s GDP growth in the 1st quarter of 2019 was 6.4% – the
same as in the last quarter of 2018. This figure, and other economic data
released at the same time, refuted predictions of sharp economic downturn in
China made in the Western media.

The Financial Times
headline regarding the first quarter’s results was ‘China GDP grows faster than
expected in first quarter’ – by which it meant faster than the FT had expected!
The Wall Street Journal’s headline
similarly was ‘China Growth Beats Expectations… Many economists prepared for a
weaker first-quarter performance’ – by which it meant economists the Wall Street Journal had paid attention
to had expected a weaker performance.

In reality, however, there was no need to anticipate any
unacceptable slowing of China’s economy provided that current trends were
correctly understood.

First, appropriate short-term stimulus measures had already
been taken and are working their way through the economy.

A significant credit stimulus has been given. Bank lending
was 1.7 trillion yuan ($254 billion) in March compared to 0.9 trillion ($135
billion) in February. Total social financing increased by 2.9 trillion yuan
($433 billion) in March compared to 0.7 trillion yuan ($105 billion) in
February. The effect of this stimulus was shown in the good data for March –
with an 8.5% increase in industrial production, the best since 2014, and an
8.7% increase in retail sales. Exports in March rose by 14.2% year on year in
dollar terms.

China’s official manufacturing PMI rose from 49.2 in
February to 50.5 in March. The Caixin manufacturing PMI, more weighted towards
smaller firms, rose from 49.9 in February to 50.8 in March. The official
non-manufacturing PMI strengthened its expansion from 54.3 to 54.8.

This strengthening data in March is particularly good in
light of the international slowdown being predicted by the IMF and other
international economic organisations.

The IMF projects that GDP growth in the advanced economies
as a whole will fall from 2.3% in 2018 to 1.8% in 2019. The slowdown in the
largest Western economic centres is estimated to be even greater. The IMF
projects that EU growth will fall from 2.1% in 2018 to 1.6% in 2019, a decline
of 0.5%, and US growth will fall from 2.9% to 2.3% in the same period – a
decline of 0.6%. As the growth rate of the Western economies is much slower
than China this means that this slowdown in the US and EU is proportionately
much greater compared to its starting point than in China.

But in addition to these short-term trends in China’s
economy what is even more important for the medium term was the turnaround in fixed
investment. The rise in fixed asset investment was 6.3% year on year – up from
6.1% in the previous month and from a low point of 5.3% in August 2018.

The reason this is crucial is set out in the article below.
It shows in a detailed way that it is investment, and not any other major
factor in the economy, which controls China’s rate of economic growth – as it
does in other major economies. In addition to its medium-term effect it was the
fall in fixed investment which led to the economic slowdown in the second half
of 2018, and the upturn which led to the good results in the first quarter of
2019 and in March in particular. Quantitative analysis of the data therefore
confirms that it is fixed investment which is the most powerful factor in
China’s medium-term economic development and its short-term macroeconomic
regulation.

The article below was written before the publication of the
first quarter 2019 economic data in order to analyse current US policy towards
China and China’s economic slowdown during 2018. Its conclusion was clear
‘policies which affect capital inputs into China’s economy, that is investment’
have the most powerful effect in ‘lowering, sustaining or raising China’s
economic growth rate.’ But the new economic data for the first quarter of 2019
strongly confirms the analysis of the article. The analysis in the article
therefore deals with both short term and medium-term trends in China’s economy.

The economic context of current US policy towards China

US
trade policy towards China has not only economic but directly geopolitical
goals. The latter is to attempt to slow down China’s economic development to
the point where this creates problems for the Communist Party of China (CPC). As
the Wall Street Journal,
put it, openly hoping for this result: ‘China’s economy is slowing, which could
dent support for Communist Party leadership.’. This key journal of US hard
liners expressed fear that in the China-US trade negotiations there was a
danger of: ‘a deal that won’t lead to fundamental changes by China, including
reducing the power of its state-owned enterprises.’ This latter goal, however, was a means to another
end. As the Wall Street Journal
summarised it in another article regarding
the aims of US anti-China hardliners, they were: ‘focussed on steps forcing
China to give ground on issues it sees as crucial to maintaining the Communist
Party’s rule.’

The Washington Post, one of the most influential US political newspapers, put it similarly urging a hard-line: ‘One of the main points of contention in the protracted trade discussion has been the role of China’s state-owned enterprises.’ It noted: ‘Trump is demanding… a sweeping overhaul of China’s economy a key condition for ending the U.S.-China trade war…. Securing… assent to abandon the economic model that lifted China… to become the world’s fastest-growing major economy would crown Trump’s confrontational diplomacy with success.’ Its conclusion was the same hope as the Wall Street Journal, that economic policies could be imposed by the US on China which would weaken the position of the Communist Party: ‘Trump’s hopes of winning genuine structural changes in China’s economic model are colliding with…. preserving Communist Party control.’

This geopolitical
goal, disguised as an economic one, is adopted because US anti-China forces accurately
understand that the CPC is the core of the People’s Republic of China (PRC) and
the rejuvenation of the Chinese nation. Therefore, anti-China forces believe that,
in the same way that the overthrow of the CPSU led to the collapse of the USSR,
and a historic geopolitical catastrophe for Russia, if they could weaken the
CPC then they would be able to impose a similar historic defeat on China –
blocking China’s national rejuvenation.

Under those circumstances, when an economic policy is being pursued with a geopolitical goal which is against the interests not only of China but of the world, it is therefore important that there is an accurate understanding of economic forces which are operating. China can no more escape economic laws than any other country. If there is an accurate understanding of the economic forces operating, there will therefore be the greatest ability to deal with any negative pressures from outside China. Equally, if there is a misunderstanding of the economic processes operating, rhetoric or effort will not be able to avoid the negative consequences.

Valuable
articles by other economists have concentrated on questions such as demand
management while the focus of this article is the medium/long term supply side
of China’s economy. These two approaches are not contradictory – both demand
and supply sides of the economy must be analysed, and demand measures may in an
important number of cases be more rapid in their effect. It should simply be
noted that in the medium/long term the supply side of the economy dominates and
in the shorter-term demand measures must necessarily operate through creating
changes on the supply side. That is, to produce changes in economic growth,
demand must lead to changes in economic inputs – changes in demand which do not
affect supply side inputs may produce inflation or deflation, but they do not
produce changes in economic growth. Therefore, it is also necessary to analyse
the supply side in order even to assess the impact of demand side measures. This
article’s aim is to therefore to analyse in a quantified way the fundamental
supply side forces operating in China’s economy.

China’s per capita GDP growth is the fastest of any major economy

To avoid
any misunderstanding in what follows, it is necessary to have a strictly
balanced analysis of the situation of China’s economy. In 2018 China had the
fastest per capita GDP growth of any major economy – a position it has held for
decades. Figure 1 shows that on the IMF’s
estimates China’s per capita GDP growth in 2018 was 6.1% compared to India’s
5.9%, 2.2% in the US, 1.8% in Germany and 1.4% in Japan. As analysed below the
fact that China’s population growth is now significantly lower than India, the
US, the UK, and Canada, to make comparisons simply among major and G7 economies,
necessarily affects China’s ranking as measured by total GDP growth. But the
well being of China’s population depends more on per capita GDP than on total
GDP. To take one example, even if India’s official GDP figures are accepted,
and they are not by many experts even in India, China’s per capita GDP growth
is still faster than India’s – and China’s per capita GDP growth is almost
three times as fast as the US, more than three times as fast as Germany, and
more than four times as fast as Japan.
Talk
in the Western or Chinese media that China’s economy is in ‘deep crisis’ is
therefore merely empty propaganda – as with similar claims made for decades.
Furthermore there is no reason to believe that either in the short or medium
term such a crisis will develop – China has the strongest macro-economic
mechanisms in the world for preventing a severe economic slowdown, as analysed
in my book 别误读中国经济 (‘Don’t
Misunderstand China’s Economy’). The issues in this article therefore do not to
deal with such non-existent ‘crises’ but primarily deal with clarifying medium/long
term issues on which it is important to avoid conceptual or factual confusion.

Testing explanations of China’s economic slowing

There
are currently three popular explanations of China’s economic slowing appearing
in the media which are examined here against the test of facts.

That the slowing of China’s economy is due to lack of proper market mechanisms, a claimed negative effect of SOEs in the economy etc.

That China’s economic slowing is due to demographic factors, a slowing of the growth of the working age population followed by its slow decline.

That China’s economic slowing is due to a decline in capital inputs.

These
explanations, as will be seen, are not mutually exclusive. However even when more
than one process is operating it is crucial to find out which are the most
powerful – as only by dealing with the most important of these can an adequate
policy response be developed.

The
conclusions arrived at from study of the facts are clear:

Demographic factors play some, but a small, role in the
slowing of China’s economy.

Factors such as inefficient market mechanisms, or SOEs
play essentially an insignificant role in China’s economic slowing – although
maintaining the efficiency of market mechanisms is crucial to prevent an
excessive slowing of China’s economy.

The overwhelmingly dominant factor in China’s economic
slowing is the decline in capital creation and the fall in net fixed capital
investment.

As
these issues are crucial for China’s economic development this article examines
these issues in a comprehensive way.

The necessity to use the most accurate data

To accurately
analyse the processes operating in China’s economy it is vital to use real, and
the most accurate possible, data. It is not unusual to see articles in parts of
the media, which consists of ‘lists’ of issues without accurately analysing the
real weight of each. It is indeed not unusual in parts of the media to see
articles which contain no quantified data on trends in the economy but merely
non-quantified claims. This is not
merely wrong in principle but dangerous. Because by this method even if a real
issue is pointed to, then if its real weight in the situation is not measured
accurately this can lead to misleading judgements and consequences.

To
explain this an analogy can be taken – comparing China’s economic development
to a scientist analysing the path of a billiard ball across a flat table. If
the scientist has ultra accurate measuring instruments it will be found that
the trajectory of the ball is affected by innumerable forces – the gravity of
the moon, the gravity of other planets, even the gravity of distant galaxies.
The scientist is therefore stating something true if they say, for example: ‘I
have found the trajectory of the billiard ball is affected by the gravity of
the planet Mars.’ But, unfortunately, emphasising this true statement can lead
to pseudo and misleading arguments. Because, if the scientist focuses only on
the effect of Mars’s gravity on the billiard ball or says, ‘the trajectory of
the ball is affected by the gravity of Mars, this is therefore the big issue to
analyse’ or does not mention other forces, they are saying something
fundamentally untrue – by far the most powerful force acting on the ball is the
gravity of the planet Earth. Therefore, a statement which is true can be deeply
misleading if its real weigh in the situation is not calculated.

This
principle strongly applies to economic development. Innumerable factors affect
economic growth, but it is necessary to accurately measure which are the most
powerful and which less powerful. It was to accurately measure the weight of
different factors in economic growth that the key tools of factual economic
analysis were developed – growth accounting, national accounts statistics etc.

The
practical consequences are obvious. If emphasis is placed on dealing with the
less powerful factors in economic development, then even success in tackling
these will not deal adequately with problems nor take advantage of economic opportunities.
Only if the most powerful forces in economic development are dealt with can
economic problems be solved, and opportunities successfully taken advantage of.

For
this reason, this article concentrates on factually analysing the most powerful
factors in the China’s economy – the policy implications are examined at the
end of the article.

Growth accounting

The
most accurate modern method to calculate the weight of different causes of
economic growth is ‘growth accounting’ as originally developed by Robert Solow.
Solow’s original formulation, however, suffered from two errors – it did not
calculate the effect of changes in the quality of labour (education, training
etc) and it did not calculate changes in the quality of capital (reflected in different
rates of depreciation of capital). The necessary corrections to these measures were
therefore subsequently introduced and adopted by the statistical services of
the US, OECD and other international organisations.

TFP
is defined as that part of GDP growth which cannot be explained by either
capital or labour inputs.

Using
a growth accounting framework, the real importance of popular explanations of
the slowing of China’s economy can be easily factually analysed in terms of their
effect on economic inputs.

If the argument is accurate that slowing of China’s economy is due to lack of proper market mechanisms, a negative effect of SOEs etc., this would show in a slowing of TFP growth – as market efficiency, the existence of SOEs etc are issues of efficiency/productivity not issues of capital or labour inputs.

If the argument that China’s economic slowing is due to demographic factors is accurate, i.e. due to negative shifts in the growth of working age population, this would be reflected in a slowing of labour inputs.

If the explanation is correct that China’s economic slowing is due to a fall in investment this would be reflected in a decrease in capital inputs.

To analyse
the factual situation regarding these inputs into China supply side, Figure 2 therefore shows the trends in China’s
capital inputs, labour inputs, and TFP since 1990. As China’s response to the
international financial crisis, and the framework for analysing the slowing of
its economy, may be considered as starting in 2009 therefore the focus is
comparing the situation in that year with the latest available data.

The
key facts from growth accounting are clear. Between 2009 and 2017 China’s GDP
growth fell by 2.3%. Breaking this down in detail:

There was a small reduction in labour inputs, almost certainly primarily due to demographic factors, which diminished GDP growth by 0.2% a year. Calculated as proportion of the total slowing in China’s economy, 11.6% of the deceleration in GDP growth is due to the decline in labour inputs.

There has been essentially no change in TFP growth – calculated to two decimal points TFP contributed 3.23% GDP growth in 2009 and 3.26% in 2017 (the increase from 3.2% to 3.3% in Figure 2 is merely due to a changing in the rounding of decimals).

The reduction of capital inputs into China’s economy was from creating 5.1% GDP growth in 2009 to 3.0% GDP growth in 2017 – i.e. the fall in capital inputs reduced China’s GDP growth by 2.1%. The growth of GDP due to capital inputs fell by 41% between 2009 and 2017, accounting for 89.6% of the decline in GDP growth.

Therefore,
evaluating the various popular theories regarding the slowdown in China’s GDP
growth:

The overwhelming factor in the fall in China’s GDP growth was the decline in capital inputs – which accounted for almost 90% of the decline in China’s GDP growth.

There was a fall in labour inputs, primarily due to demographic factors, but this accounted for only slightly over 11% of the decline in China’s GDP growth.

There was no significant change in China’s TFP growth – i.e. there is no evidence that the slowdown in China’s economy was primarily due to deterioration in market efficiency, or a negative role of SOEs, all of which would show up as a decline in TFP growth.

In
summary, the overwhelming reason for the slowing of China’s GDP was a fall in
capital inputs, which accounted for about nine tenths of the decline; there was
a contribution from demographic factors, accounting for approximately one tenth
of the fall in GDP, and there was no significant indication the slowdown was
due to a decrease in market efficiency or the role of SOEs – which would show
as a decline in TFP.

Fall in labour inputs- demography

Having
examined the overall factual data, applying the famous Chinese dictum of ‘seek
truth from facts’, the significance of the individual processes affecting the
slowing of China’s economy may now be seen.

The
first is that it is true that demographic factors play a role in China’s
economic slowing – but it is a small one, accounting for only slightly over one
tenth of the decline in the growth rate. Therefore, arguments that the slowing
of China’s economy are primarily due to demographic factors, in the most
extreme version that ‘China will get old before it gets rich’ will not
withstand factual examination. As will be noted below this conclusion from
growth accounting is fully confirmed by national accounts calculations –
leaving no doubt as to the factual situation.

In
terms of a precise analysis, it would theoretically be possible to maintain
labour inputs even within existing demographic trends – this could be achieved
by methods such as raising the retirement/pension age, by increasing the education
and skill of the labour force etc. However, these would either involve very
major social changes, e.g. the retirement/pension age is extremely sensitive in
all countries, or it would require very large expenditures – for example, in
expanding the education and training system. Some measures in these fields are
therefore to be anticipated but it is improbable that these could fully offset
demographic trends.

Therefore,
it is accurate to state that some slowing of China’s growth rate due to demographic
factors will occur. But the factual data shows that this has been a relatively
small factor in China’s economic slowing. Claims such as that ‘China will get
old before it gets rich’ are highly exaggerated as the facts show that trends
in labour inputs/demography account for only a small proportion of China’s
economic slowdown.

A relevant
conclusion from demographic trends, however, is that slow growth of China’s
population confirms that the most relevant criteria for measuring China’s
comparative economic development is per capita GDP. China’s 0.5% population
growth in 2018, is significantly slower than India’s 1.3% or the US’s 0.7%. But
the economic wellbeing of China’s population is more directly related to per
capita GDP than to total GDP. Data showing that China has the most rapid per
capita GDP growth of any major economy was given at the beginning of this
article.

TFP

The
application of up to date internationally approved methods of measuring the
causes of economic growth, as noted above, shows clearly that it is a decline
in capital inputs which is primarily responsible for the slowing of China’s
economic growth – and not factors such as the role of SOEs or lack of market
efficiency. Nevertheless, this does not mean that factors which affect TFP are
not significant. Indeed, one of the reasons for China’s extremely rapid per
capita GDP growth is its very rapid growth of TFP – by far the fastest for any
major economy. Figure 3 shows that in 2017, the latest
year for which there is data, China’s increase in GDP due to TFP growth was
3.3% compared to 1.8% in India, 1.3% in Canada, and 0.6% in Germany – the
equivalent figure in the US was only 0.3%.

To
confirm that China’s rapid TFP growth was not merely due to the specific
situation in 2017, Figure 4 shows the annual average
increase in GDP due to TFP growth for the major economies for the period
2009-2017. This shows no difference to the figure for 2017 for China of 3.3%
and India at 1.8%. But the TFP growth in the G7 economies in this period was
far lower – only 0.2% in Germany and 0.1% in the US, while in three G7
countries TFP growth was actually negative.

Numerous
implications flow from these international comparisons. But one of the most
important is that it is unrealistic to believe that China can accelerate its
GDP growth by increasing its rate of TFP growth. On the contrary, China’s rate
of TFP growth is so much higher than other major economies that it will take
considerable effort to prevent China’s rate of TFP growth falling, with
negative consequences for its overall economic growth rate.
However,
as the relation of TFP growth and economic growth is misunderstood in parts of
China’s media, and it is suggested that a policy attempting to increase TFP
growth is an alternative to one based on maintaining capital inputs, this issue
will be examined in detail.

TFP growth is pro-cyclical

Analysing the slower TFP growth in the G7 economies during the period 2009-2017, compared to the sustained TFP growth in China and India, relates to a feature of TFP growth which is crucial for China. It is sometimes suggested in sections of the media that China should follow a strategy of slower GDP growth in order to focus on increasing TFP. There are several errors in such a concept, but one of the most significant is that it simply will not work practically because international studies, and analysis of China, show that TFP growth is ‘pro-cyclical’ – i.e. faster GDP growth leads to faster TFP growth while slower GDP growth leads to slower TFP growth.

This
situation is clear from both international comparisons and data for China
itself. The OECD publishes regular systematic international comparisons of TFP
growth, all of which confirm that TFP is ‘pro-cyclical’ – i.e. TFP growth increases when the economy is
speeding up and TFP growth declines when the economy is slowing down. Therefore, slowing China’s economy would be
expected to lead to slower TFP growth not faster.

The
OECD uses the term Multi-Factor Productivity (MFP), instead of the term TFP utilises
by Solow and other creators of economic growth accounting, but the concept is
identical. The conclusion of the OECD in its Latest 2018 report is unequivocal:
‘multifactor productivity growth (MFP) behaves cyclically, i.e. it increases in
upturns and declines in downturns… The empirical evidence confirms the cyclical
pattern of MFP. In fact, MFP follows GDP growth very closely, not only in terms
of direction but also in terms of the size of the change.’ This confirms the
finding of all previous OECD studies – as shown in the appendix to this article.

One reason some writing in the media has failed to note this ‘pro-cyclical’ behaviour of TFP is that it erroneously believes TFP represents ‘technological change’ – which would not be expected to show a cyclical behaviour. But such a view is a misunderstanding of what TFP measures. As the OECD notes in the 2017 edition: ‘After computing the contributions of labour and capital inputs to output growth, the so‐called multifactor productivity can be derived. It measures the residual growth that cannot be explained by changes in labour and capital inputs and represents the efficiency of the combined use of labour and capital in the production process. Multifactor productivity is often perceived as a pure measure of technical change, but, in practice, it should be interpreted in a broader sense… Changes in multifactor productivity reflect also the effects of changes in management practices, brand names, organisational change, general knowledge, network effects, spillovers from one production factor to another, adjustment costs, economies of scale, the effects of imperfect competition and measurement errors.’

TFP growth in China

It
follows from these general international comparisons that allowing slowing of
China’s economic growth will be accompanied by slowing TFP growth. But it is,
of course, also necessary to check that this general international finding also
applies to China.

Analysis
of the correlation of TFP growth and GDP growth in China confirms that it is
fully in line with the international findings of the OECD given above – i.e.
the speeding up of GDP growth is correlated with increasing TFP growth, and a
slowing GDP growth is correlated with slowing TFP growth.

Figure 5 shows the annual correlation
between China’s annual GDP growth. This correlation, of 0.85 is extraordinarily
high and fully in line with the OECD’s international conclusions. To cross
check that this correlation is not due to purely short term factors, in the appendix
to this article Figure 18 shows the correlation of China’s
GDP growth with TFP growth using a three year moving average, and Figure 19 uses a five year moving average.
The correlations shown, 0.81 in both cases, are also extraordinarily high.
The
conclusions of this are therefore clear. There
is nothing unusual in China’s economic development – it is in line with international
data. As with other countries its TFP growth is pro-cyclical. Therefore,
any policy based on slowing China’s economy to attempt to accelerate TFP growth
will not work as this will exert downward pressure on China’s TFP growth. On
the contrary, it follows from the pro-cyclical character of TFP growth that it
is an upturn, an acceleration in China’s economic growth, that aids increased
TFP growth.

It
may, of course, be noted that correlation is not the same as causation. The
fact that fast GDP growth is correlated with fast TFP growth does not prove
that fast GDP growth causes fast TFP growth, or that fast TFP growth causes
fast GDP growth, or that some other factor(s) causes both fast GDP growth and
fast TFP growth. But for present purposes it should be noted that it is
unnecessary to establish the direction of causation. It is merely necessary to
note that the correlation of the speed of GDP growth and of the rate of increase
of TFP is over 80%. Such a high
correlation means that faster TFP growth cannot be achieved without faster GDP
growth.

Therefore,
the perspective that there can be fast TFP growth without fast GDP growth is
unrealistic – whether considered from the point of view of international
comparisons, as studied by the OECD, or whether considered in the specific case
of China. Even less realistic is the idea that TFP growth can be accelerated
while GDP growth slows.

It
should be clearly noted from this that it does not follow that slower GDP
growth may not help in achieving other ‘quality’ targets. For example, China
has achieved notable success in environmental improvements, in lowering
pollution and reducing energy consumption per unit of GDP. Achieving these
targets may be achieved through slower GDP growth. However, it is clear from
both international comparisons and the experience of China that slower GDP
growth will not aid in achieving high TFP growth. On the contrary both
international experience and that of China shows slow GDP growth will lead to
slower TFP growth.

Alternative estimates of growth inputs

It
should be noted that the above data uses China’s official calculation of its
growth rate. Attempts are sometimes made in the West to claim that China’s real
GDP growth is systematically exaggerated and in reality is far lower than the
official data – although top Western experts who have examined this such as Tom
Orlik, whose Understanding China’s
Economic Indicators is the most thorough study of China’s economic
statistics, do not agree with this assessment. Most such Western claims are unsystematic
and such methods therefore cannot be used to thoroughly examine China’s growth. However, one systematic attempt to examine
China’s growth using modern growth accounting methods, with a claim that
China’s growth is much slower than its official data, has been made – by Harry
X. Wu of the Institute of Economic Research, Hitotsubashi University, Tokyo.
This claims that between 2009 and 2017 China’s annual GDP growth fell from 7.9%
to 3.7%. But this also finds that the overwhelming reason for this claimed
slowdown was due to decline in capital inputs. Wu’s calculations show that
between 2009 and 2017 annual GDP growth due to labour inputs fell by 0.1%,
annual GDP growth due to TFP fell by 0.1%, but annual GDP growth due to capital
inputs declined by 3.9%.

Therefore,
even if it is claimed that China’s GDP growth is lower than official data, use
of modern growth accounting data shows that the overwhelming reason for the
slowdown in China’s economy is not due to changes in TFP or demography but due
to a decline in capital inputs

National accounts data

So
far modern growth accounting data has been used for analysis – growth
accounting is necessary if TFP is to be calculated. This showed that the
overwhelming reason for the slowing of China’s economy is the decline in
capital inputs. However, while growth accounting is the most accurate method of
calculating contributions to changes in GDP there are strong reasons for cross
checking the results with other statistical data:

If other data, for example national accounts statistics, corroborate the findings of growth accounting this would strongly confirm the certainty of the findings.

Growth accounting requires a great deal of data for computation. There is therefore a delay in such data becoming available – such data for China is only available to 2017. More data for China is, however, available from other statistical sources.

As other
such data is less accurate than growth accounting, if changes that other
statistics demonstrated were small in scale, or contradicted growth accounting
data, then it might create difficulties to interpret the results. Fortunately
for present purposes, however, examination of national accounts and other
statistics shows trends which are not small in scale and are fully in line with
growth accounts data – they therefore confirm the findings of growth
accounting. Such confirmation of trends by two different statistical methods,
of course, strengthens confidence in the findings. Therefore, in order to
evaluate the impact of changes other statistical sources will also be
considered

The limited effect of demographic changes

The first trend which is confirmed by use of statistical
sources other than growth accounting data is the negative but relatively small
effect of demographic changes.

It was already noted that China’s retirement/pension age
is very low by international standards – which represents a policy/social choice.
The international definition of working age population is 15-64 years. By this
criteria Figure 6 and Table 1 show
that between 2009 and 2017, the latest available data, China’s internationally
defined working age population rose by only 1.3%, and China’s total population
rose by 4.1%, whereas China’s GDP rose by 84.3%. China’s GDP therefore rose 66
times as fast as China’s working age population and 20 times as fast as China’s
total population.

In summary, China’s population increase played a negative but small role in China’s GDP growth. Similarly, therefore, the decline in China’s working age population, which reached a peak in 2015 at 1.5% above its 2009 level and by 2017 had fallen to 1.3% above its 2009 level, will play only a small role in slowing of China’s economic growth. The conclusion of growth accounting data is therefore confirmed by other sources. Demographic factors will play a negative role in China’s GDP growth, but this effect will be small. Claims such as ‘China will grow old before it grows rich’ are based on gross exaggerations and have no serious factual basis. The primary source of any slowing of China’s GDP slowing must therefore be sought in entirely different factors than demographic ones. The fact that both growth accounting and other data leads to exactly the same conclusion leaves no doubt as to the factual situation.

Fall in Net Capital Creation

Turning
to capital inputs, national accounts data fully confirms the fall in China’s
capital inputs shown by growth accounting. Figure 7 shows that China’s net fixed capital
creation (i.e. gross fixed capital formation minus depreciation) fell from
30.5% of GDP in 2009 to of 21.5% of GDP in 2016 (the latest available
internationally comparable data) – this is a very large 9.0% of GDP fall.

Indeed,
at a first approximation the relation between the reduction in China’s net
investment and the slowing of the economy is even rather mechanical. In 2009-2016
China’s annual GDP increase fell from 9.4% to 6.7%. This is a reduction of 29%
compared to the initial figure, while net fixed capital formation fell from
30.5% of GDP to 21.5% – a reduction of 29% compared to the initial figure.

Figure 8 fully confirms the extreme
closeness of the correlation between the decline in China’s net fixed capital
formation and the slowing in GDP since 2009. The linear correlation is 0.76, by
itself extremely high. However, there is no necessity for
a correlation to be linear and Figure 9 shows that the non-linear correlation is 0.81 –
extraordinarily high.

The usual
caveat that correlation by itself does not establish causation is irrelevant
here, as the extremely high correlation shows that it is not possible to
increase China’s GDP growth without increasing the percentage of net fixed
capital formation in GDP – and that any decline in the percentage of China’s net
fixed investment in GDP will be accompanied by an economic slowdown.
The
extremely close correlation between net fixed investment and economic growth shown
by the national accounts data is therefore fully in line with growth accounting
calculations analysed earlier. Capital inputs are overwhelmingly strongly correlated
with China’s economic growth.

Gross capital formation and depreciation.

If
the reason for this sharp fall in China’s net capital formation is now analysed
further Figure 10 shows this is due to two
processes. On World Bank data:

Approximately
one quarter, 24%, of the fall in the proportion of net fixed capital
formation in China’s GDP is due to the decline in the percentage of
China’s GDP devoted to gross fixed investment – which dropped from 44.9%
of GDP in 2009 to 42.8% of GDP in 2016.

Approximately three quarters, 76%, of the fall in the
proportion of net fixed capital formation in China’s GDP is due to a rise in
fixed capital consumption (depreciation) in China’s GDP. This is strongly
affected by the rise China’s capital stock – capital consumption as a
percentage of China’s GDP rose from 14.4% of GDP in 2009 to 21.3 of GDP in
2016.

It should be noted that an increase in consumption of
fixed capital/depreciation in GDP is a normal process resulting from an
increase in and modernisation of capital stock – it also occurs in the US. However,
the increase in the percentage of GDP ascribed to capital
consumption/depreciation in China is extremely high in terms of international
comparisons. It would therefore be important for studies to be carried out to
see if this figure is accurate or exaggerated.
Nevertheless,
the present data is so high that it indicates that capital
consumption/depreciation is a significant factor in China fall in net capital
creation – making it important to analyse net fixed capital creation and not
only gross investment.

The most recent trends in fixed investment

Data
for China’s gross fixed capital formation using national accounts data is
available to 2017, and for net capital formation to 2016. However, data for
2018 for these categories will not be available for some time. Nevertheless for
2018 statistics for year on year changes in urban fixed asset investment leave
no doubt that the same trend has continued.
Figure
11 shows that the annual
increase in China’s fixed asset investment fell from 7.2% in December 2017, and
8.1% in December 2016, to 5.9% in December 2018. As this latest figure is
significantly below China’s growth of GDP at current prices in 2018 it is extremely
likely that the percentage of fixed investment in China’s GDP declined in 2018
– continuing the trends in a fall in capital inputs shown in national accounts
data. This trend then turned around in the first quarter of 2019, with a rise
to a 6.3% year on year increase in fixed investment. Underpinning the improved
economic trends in that period.

Saving

Turning from changes in fixed investment to overall trends in China’s capital creation/saving, which is necessary to finance investment, the same trends can be seen – only in an even more extreme form. It should be noted for clarity that throughout this article by ‘saving’ is meant China’s total savings – the sum of household saving, corporate saving, and government saving – and is not only household saving.

Figure 12 shows that China’s net saving, which is equivalent to China’s net capital creation, fell from a peak of 39.3% of Gross National Income (GNI) in 2007, to 36.7% of GNI in 2009, to 24.9% of GNI in 2016 – i.e. a decline of 11.8% of GNI in 2009-2016, and 14.4% of GNI in 2007-2016. This extremely large fall in the percentage of net saving in China’s economy, a large decline in the capital supply, is necessarily a strongly negative supply side shock for China’s economy.

Analysing
in greater detail this major fall in China’s net saving, i.e. net capital
inputs, again shows this is due to two processes:

China’s
gross saving fell from 51.2% of GNI in 2009, and a peak of 51.8% of GNI in
2007, to 46.2% of GNI in 2016. This accounted for 42% of the fall in
China’s net saving between 2009 and 2017.

Capital
consumption has risen from 14.5% of GNI in 2009, and 12.4% of GNI in 2007,
to 21.3% of GNI in 2016. This accounted for 58% of the fall in China’s net
saving between 2009 and 2017.

As
already noted, estimates of savings/capital consumption are difficult to
calculate but the changes shown are so large as to leave no doubt as to the
general trend. There has been a sharp reduction in the proportion of China’s
economy devoted to net capital creation.

This
measured trend, paralleling the decline in capital inputs measured by growth
accounting, is equivalent to a severe negative supply side shock to the
economy. It is as though the petrol was drained out of the fuel tank of a car,
making it inevitable that the car will not run for the same distance as before.
Anyone expressing surprise that the car will not run as far as before is simply
going against the laws of physics.
Put
in economic terms what has occurred is a reduction in the capital supply to China’s
economy which is clearly confirmed by both growth accounting and national
accounts data. As capital is one of the key inputs to the economy, such a
reduction will necessarily produce economic slowing.

The correlation of China’s saving and economic growth

It
was earlier shown that the correlation between China’s net fixed investment and
its rate of GDP growth was extremely high. Net fixed investment is that part of
China’s capital creation used for increases in fixed investment/capital stock
in China. However, while fixed investment accounts for by far the largest part
of use of China’s savings (gross fixed investment is approximately nine tenths
of the use of China’s capital creation) small parts are used for other purposes
– accumulation of inventories or as the surplus in China’s balance of payments.
Therefore, for exactitude it is important to also study the correlation between
China’s total capital creation/saving and GDP growth.

Such
analysis is extremely revealing. It shows that the correlation between China’s
capital creation/saving and its economic growth is even closer than between net
fixed investment and economic growth. Furthermore, there is an extremely strong
correlation between China’s gross savings and its GDP growth – whereas the
correlation between China’s gross fixed investment and economic growth is low. This
is statistically highly useful as it avoids the issue noted above that the
calculated consumption of fixed capital/depreciation in China is very high compared
to other countries. The fact that an extremely strong correlation of China’s gross
capital creation/saving with GDP growth exists, as well as between net capital
creation/saving and GDP growth, means that any complications of calculating
capital consumption/depreciation can be avoided.
Analysing
first the linear correlation of gross saving and economic growth this is shown
in Figure
14. This correlation of 0.84
is extremely high.

However,
as already noted there is no necessity for a correlation to be linear. Figure 15 shows that the non-linear
correlation is of gross saving and 0.87– an extraordinarily high correlation.
As
before the caveat that correlation does not establish causation is irrelevant
as the extremely high correlation shows that it is not possible to increase
China’s GDP growth without increasing the percentage of gross saving in GDP – and
that any decline in the percentage of gross saving in GDP will be accompanied
by an economic slowdown.

Turning
to net saving, Figure 16 shows that the linear
correlation of the percentage of net saving in China’s GDP with its economic
growth is 0.88 – an ultra-close connection.

Turning to the non-linear correlation of the percentage of net saving in China’s GDP and its economic growth Figure 17 shows that this is 0.91 – an extraordinarily high correlation.

Once again the usual caveat that correlation does not establish causation is irrelevant as this extremely high correlation shows that it is not possible to increase China’s GDP growth without increasing the percentage of net saving in GDP, and that any decline in the percentage of net saving in GDP will be accompanied by an economic slowdown.

Capital creation and China’s economic growth

As it
may be seen that the correlation between China’s capital creating/savings and
economic growth is even closer than between net fixed investment and economic
growth, it may be asked why this is the case?

This
difference is not of crucial importance for economic policy, as both
correlations are extremely high, confirming that it is capital creation which
is the dominant issue in China’s economic growth. But it may be noted that China’s
total supply of capital, measured by capital creation/savings affects other
features of the economy than fixed investment. For example, a reduction in
capital creation will necessarily produce negative consequences in specific
markets – upward pressure on interest rates, decreasing profitability of
companies, increase in leverage due to the fall in company profitability etc. These
other negative effects of the fall in capital creation/saving may explain why
the correlation of this with China’s economic growth is even stronger than the
relation to fixed investment.

Conclusion

As emphasised
at the beginning of this article there is no ‘deep crisis’ in China’s economy –
China’s per capita GDP growth continues to be the fastest of any major economy
in the world. This is the crucial international framework to understand. Within
that overall perspective the conclusion of both modern growth accounting and
national accounts measures regarding why China’s economy has slowed are the
same.

The overwhelming cause of the slowing of China’s economy
is a fall in capital/investment creation. This is shown in growth accounting by
the fact that almost nine tenths of the decline in GDP growth is due to a fall
in capital inputs. In national accounts data it is confirmed by the extraordinarily
high correlation between net fixed investment and GDP growth of 0.81, of a
correlation between gross saving and GDP growth of 0.87, and a correlation
between net saving and GDP growth is 0.91 – all extraordinarily high figures.

Demographic trends will reduce labour inputs, slowing the
economy, but this effect only accounts for a small part of economic deceleration
– macro-economic data shows that increased labour inputs created only a small
part of China’s growth, while growth accounting shows a fall in labour inputs
accounts for only about one tenth of the slowing of China’s economy.

Growth accounting data shows that China’s TFP growth is
high in terms of international comparisons – meaning it is very unlikely that
China’s GDP growth can be accelerated by an increase in TFP, but that measures
will have to be taken to ensure China’s TFP growth does not fall.

It is
necessary to be aware of the full scale of this negative supply side shock in
terms of capital creation. The decline in China’s net fixed capital investment
is 9% of GDP on World Bank data. Even if the statistics on capital depreciation
merit further evaluation, given their extremely high level by international
standards, even measures of gross savings, which do not rely on calculation of
depreciation, has fallen by 5.0% of GDP. Either figure is a severe negative
supply side shock – confirming the growth accounting data which shows a sharp
fall in capital inputs.

To
return to the beginning of this article, the focus here is on medium/long term
factors in China’s economic development. This is not contradictory to a shorter-term
emphasis on demand management or supply side measures already taken to close
excess capacity. However, to note again, measures affecting the demand side of
the economy must necessarily operate through their impact on the supply side
i.e. to produce changes in economic growth demand must create changes in labour
inputs, capital inputs or TFP. Changes in demand which do not affect the supply
side inputs may produce inflation or deflation, but do not produce changes in
economic growth.

The
consequences of this factual situation of the weight of factors in China’s
economic development for economic policy are clear. As for reasons already
stated TFP will be at best neutral, and demographic trends will be moderately negative,
the only key input which can positively influence China’s growth rate is the
level of capital inputs. This means that policies which affect capital inputs
into China’s economy, that is investment, can have a powerful effect in lowering,
sustaining or raising China’s economic growth rate.

This quantitative
situation therefore also necessarily determines the practical efficacy of
measures designed to limit China’s economic slowdown and/or to carry out any
economic stimulus.

Measures to maintain or increase market efficiency are
important to try to sustain China’s rate of TFP growth but they not quantitatively
able to prevent an economic slowdown – for the reasons given it is extremely
improbable China could increase its level of TFP growth given its present high
level. Furthermore, a strategy, which is sometimes proposed that China should
allow its economy to slow but increase its TFP growth will not work for the
quantitative reasons outlined – TFP growth is pro-cyclical and therefore a
slowdown in economic growth will lead to a slowing of the TFP growth.

Demand side measures to increase consumption will only be
successful, for the reasons already outlined, if they produce changes on the
supply side – that is, primarily if they affect capital inputs.

Measures to cut company taxation are useful in
maintaining employment and other goals but for the quantitative reasons
analysed above they will only translate into faster economic growth if they
lead to an increase in capital inputs – that is investment.

In summary, given the quantitative situation analysed
with demography/labour inputs and TFP, only measures which directly increase
capital inputs, that is either state or private investment, will be significantly
beneficial to the economic growth rate.

Practical
application of policy will necessarily confirm the trends analysed. While
measures such as increases in the retirement/pension age, and increases in
training and education, may decrease the negative effect of demographic changes
no significant body of opinion believes that a significant increase in China’s
growth rate can take place due to an increase in labour inputs. There are those
who argue that China’s growth could be increased due to an increase in TFP, but
for the quantitative reasons given this will not be successful. For
quantitative reasons the only method that will stabilise/increase growth will
be an increase in capital inputs.

Postscript

This article was written to analyse in detail the slowing of China’s economy in the latter part of 2018. But its conclusion, that it is the level of investment which controls the rate of growth of China’s economy, applies equally to the good results for the first quarter of 2019. The fall in investment in 2018 led to economic slowing, the rise in investment in the first quarter of 2019 led to stabilisation in GDP growth and acceleration in other economic measures. Therefore, from both angles the data fully factually confirms that it is fixed investment which is the most powerful factor affecting China’s speed of economic development.

Appendix

This appendix
is intended for economic specialists – non-specialists should know that it does
not add to the main conclusions of the article. It merely indicates further
substantiating evidence and explanations regarding the points in the
article.

First
regarding growth accounting, it is important to note the official improvements
in the methods of measuring economic growth and its causes which have been
formally adopted by the UN, OECD, and other statistical agencies – it is a
serious problem in some literature in China that methods of measuring economic
growth and its causes which are no longer accepted are used. The reasons for
these changes in the official methods of calculating economic growth and its
causes are analysed in detail in 为何联合国、经合组织与美国正式改变其经济增长成因测算方法？ (The
Copernican Revolution in Analysis of Economic Growth is Very Significant for
China). But the clearest fundamental error which had to be corrected compared
to former methods of analysing the causes of economic growth was that these did
not calculate changes in the quality of capital and labour inputs. This meant in
the case of labour, for example, that one hour of work by a South Korean
peasant in 1953, who may have been illiterate, was calculated as equivalent to
1 hour of work by a South Korean engineering PhD, and very rapidly depreciating
assets such as ICT equipment were not treated differently from assets which
depreciated over very long periods of time. These errors are corrected in the
new internationally approved methods of calculating the causes of economic
growth by:

Calculating separately labour quantity (the number of
hours worked) from labour quality (the skill, educational etc qualification of
labour);

Using the category of ‘capital services’ to measure the
contribution of different types of capital investments (in the OECD methodology
eight categories of capital assets are used ‘computer hardware,
telecommunications equipment, transport equipment, other machinery and
equipment and weapons systems, non-residential construction, computer software
and databases, research and development and other intellectual property
products.’

In this article data calculated according to these new and approved methods of calculation are used. Regarding the correlation of GDP growth and TFP growth the correlations for single years was shown in the article. However, it is useful and important to show that the same correlation exists over not merely the short but the medium term. Figure 18 therefore shows a three-year moving average for the correlation of TFP and GDP growth and Figure 19 shows a five-year moving average. The three-year correlation is 0.81 and the five-year correlation is also 0.81. Both correlations are extremely high. The caveat that correlation does not establish causation is irrelevant as this extremely high correlation shows that it is not possible to increase China’s TFP growth while reducing China’s rate of GDP growth – that is a strategy of ‘lower GDP growth and higher TFP growth’ will not work.

This finding for China is entirely in line with
international experience. In order to avoid overburdening the text with detail
for non-specialists only the 2018 OECD finding was cited. However, this is
entirely in line with all OECD studies on the issue. To show this reference to the previous OECD
studies are therefore given here.

In 2012 the Compendium of Productivity Indicators noted:
‘the empirical evidence confirms the pro-cyclical pattern of MFP. In fact, MFP
follows GDP growth very closely, not only in terms of the direction but also
the size of the change.’ (OECD, Compendium of Productivity Indicators 2012
p11.) And therefore ‘MFP behaves cyclically, i.e., it increases in an upturn
and declines in a downturn.’ (OECD, Compendium of Productivity Indicators 2012
p58.)

The 2013 Compendium of Productivity Indicators had the
same finding: ‘multifactor productivity growth (MFP) behaves cyclical, i.e., it
increases in an upturn and declines in a downturn. ‘ (OECD, Compendium of
Productivity Indicators 2013 p62).And: ‘The empirical evidence confirms the
cyclical pattern of MFP. In fact, MFP follows GDP growth very closely, not only
in terms of the direction but also in terms of the size of the change. ‘ (OECD,
Compendium of Productivity Indicators 2013 p62)

The 2015 Compendium of Productivity Indicators similarly
concludes: ‘MFP appears to have moved in a pro-cyclical way’ (p30) And:
‘multifactor productivity growth (MFP) behaves cyclically, i.e. it increases in
an upturn and declines in a downturn.’ (OECD, Compendium of Productivity
Indicators 2015 p64)

The 2017 OECD report again finds: ‘multifactor
productivity growth (MFP) behaves cyclically.’ (OECD, Compendium of
Productivity Indicators 2016 (Kindle Location 1704-1705).And that: ‘The
empirical evidence confirms the cyclical pattern of MFP. In fact, MFP follows
GDP growth very closely, not only in terms of the direction but also in terms
of the size of the change.’ (OECD, Compendium of Productivity Indicators 2017
(Kindle Location 1532).

The OECD’s factual finding is therefore clear and unequivocal. Slowing of GDP growth leads to a slowing of TFP growth. A strategy of ‘slower growth to achieve higher TFP increases’, other things being equal, therefore won’t be successful – a slowing of GDP growth will be associated with slower TFP growth.